You will be part of the team that develops the Intrusion Prevention System to power the Palo Alto Networks’s next generation firewall. The Decoder team is responsible for decoding network protocols and inspecting application traffic on enterprise customers’ networks.
Compensation
$172,100.00 - $278,300.00/yr
Responsibilities
Research networking protocols and related application networking behavior.
Research file types and file properties.
Research and provide defense mechanisms against popular protocol/firewall evasions
Develop protocol and file decoders, and integrate the detection solutions with Palo Alto Networks products
Build common services to support various network security services.
Requirements
BS/MS in Computer Science or Electrical Engineering or equivalent Military experience
Define and drive the AI performance benchmarking and workload characterization strategy across CPU, GPU, APU, NPU, and heterogeneous platforms.
Benchmark AI inference workloads using PyTorch, ONNX Runtime, vLLM, llama.cpp, TensorFlow, and related frameworks and runtimes.
Analyze key performance metrics, including latency, throughput, time to first token, tokens per second, memory utilization, power consumption, and performance per watt.
Profile workloads and identify bottlenecks across AI frameworks, runtimes, libraries, drivers, operating systems, firmware, memory subsystems, and hardware.
Lead complex root-cause analysis and recommend optimizations related to quantization, graph execution, kernels, memory usage, workload scheduling, and heterogeneous compute utilization.
Requirements
Bachelor’s or master’s degree in Computer Engineering, Electrical Engineering, Computer Science, Artificial Intelligence, Machine Learning, or a related technical field
Lead technical design, build, and demonstration of scalable AI training solutions on NVIDIA GPU hardware and software for enterprise customers.
Compensation
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 152,000 USD – 241,500 USD for Level 3; and 184,000 USD – 287,500 USD for Level 4.
Responsibilities
Work with Cloud Service Providers to design, build, and demonstrate scalable AI training solutions using NVIDIA hardware and software.
Lead technical engagements across foundation model pre-training and post-training, helping customers move from architecture and proofs of concept to production adoption.
Develop and optimize end-to-end training workflows spanning data preparation, distributed training, checkpointing, and evaluation, including reinforcement learning pipelines.
Build customer-specific proofs of concept that address critical technical and business needs, demonstrating improvements in training performance, reliability, and efficiency.
Help customers diagnose and resolve bottlenecks across GPU compute, memory, communication, networking, storage, and workload orchestration.
Requirements
BS, MS, or PhD in Computer Science, Electrical or Computer Engineering, Statistics, Physics, or a related technical field, or equivalent experience.
Nice to have: reinforcement learning from human feedback
Senior Solutions Architect to design, build, and optimize AI training solutions using NVIDIA GPU hardware and software on cloud platforms.
Compensation
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
152,000 USD – 241,500 USD for Level 3; and 184,000 USD – 287,500 USD for Level 4.
Responsibilities
Work with Cloud Service Providers to design, build, and demonstrate scalable AI training solutions using NVIDIA hardware and software.
Lead technical engagements across foundation model pre-training and post-training, helping customers move from architecture and proofs of concept to production adoption.
Develop and optimize end-to-end training workflows spanning data preparation, distributed training, checkpointing, and evaluation, including reinforcement learning pipelines.
Build customer-specific proofs of concept that address critical technical and business needs, demonstrating improvements in training performance, reliability, and efficiency.
Help customers diagnose and resolve bottlenecks across GPU compute, memory, communication, networking, storage, and workload orchestration.
Requirements
BS, MS, or PhD in Computer Science, Electrical or Computer Engineering, Statistics, Physics, or a related technical field, or equivalent experience.
Optimize and improve performance of autonomous driving context fusion software on automotive platforms.
Compensation
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
Responsibilities
Optimize context fusion software that integrates perception, map, and localization data to represent the driving environment.
Design and refine software architecture, interfaces, and data flows to meet CPU, memory, and latency requirements on automotive platforms.
Profile complex software pipelines, identify performance bottlenecks, and implement improvements backed by reproducible measurements.
Work with algorithm teams to improve computational efficiency while preserving algorithm behavior, output quality, and correctness.
Develop benchmarks and performance regression tests to track improvements and prevent regressions.
Requirements
PhD in Computer Science or related field
MS in Computer Science or related field
BS in Computer Science or related field
Nice to have: real-time software on embedded or automotive platforms
Position:
Senior Engineer (Level 1)
Job Description:
Technical Skill [Required]
Expert in C coding
Working knowledge of any one RTOS for example Micrium OS (uCOS), FreeRTOS
Working knowledge with SiLabs, STMicro, NXP controllers based on Cortex M3, M4, M0+ low power mode
Peripherals: I2C, SDIO, UART, SPI, Timers, DMA, BT, BLE
Must have working knowledge of memory optimization and low power
Good to have: Understanding of MISRA C guideline
Good to have knowledge of Radio sub GHz protocols
Soft Skills [Required]
Positive attitude
Good analytical skills
Hungry for growth
Problem solving
Quick learner
Location:
IN-MH-Pune, India-Magarpatta City-Unit A (eInfochips)
Time Type:
Full time
Job Category:
Engineering Services
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